摘要
基于稀疏恢复技术的空时自适应处理(Sparse Recovery Space-Time Adaptive Processing,SR-STAP)方法提升了动目标检测性能。然而,当出现离网效应时,SR-STAP算法的杂波抑制性能下降。为了解决离网效应问题,本文提出了一种离网误差迭代自校正STAP算法。该算法首先从常规STAP字典中选取了功率谱值较高的网格点来构建全局字典。然后,从全局字典中找到与杂波点匹配度较高的原子为中心,构建局部STAP字典,并利用贝叶斯后验概率最大思想进行局部搜索,找到与杂波点匹配度最高的网格点。最后,得到了经过修正后的STAP字典和最优STAP滤波权,优化了离网情况下STAP算法性能。通过仿真验证了所提算法消除离网误差的有效性。
Space-time adaptive processing method based on sparse recovery(SR-STAP)improves the performance of moving target detection.However,when the off-grid effect occurs,the performance of SR-STAP algorithm was degraded.Hence,an off-grid error iterative self-calibrated STAP algorithm was proposed to solve this problem.Firstly,the grid points with high power spectrum value were selected from the general STAP dictionary to construct the global dictionary.Secondly,the atoms with high matching degree with clutter points were found from the global dictionary as the center,and the local dictionary was constructed.In addition,the local search was carried out by considering the posterior Bayesian,and the clutter point with highest matching degree was founded.Finally,the calibrated dictionary and the optimal STAP filter weight were obtained,which optimizes the performance of STAP algorithm in off-grid situation.The effectiveness of the proposed algorithm was verified by simulations.
作者
尚慧慧
高志奇
黄平平
SHANG Huihui;GAO Zhiqi;HUANG Pingping(College of Information Engineering,Inner Mongolia University of Technology,Hohhot,Inner Mongolia 010080,China;Inner Mongolia Key Laboratory of Radar Technology and Application,Hohhot,Inner Mongolia 010051,China)
出处
《信号处理》
CSCD
北大核心
2021年第7期1277-1284,共8页
Journal of Signal Processing
基金
国家自然科学基金项目(61761037)
内蒙古工业大学科学研究重点项目(ZD201717)
内蒙古自治区高等学校科学技术研究项目(NJZY19072)。
